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LabelFlow Framework for Annotating Workflow Provenance

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L 4365 Esch-sur-Alzette, Luxembourg
LAMSADE Research Lab, Université Paris Dauphine, UMR CNRS 7243 Paris, France
Department of Population Health Sciences, King’s College London, London SE1 1UL, UK
School of Computer Science, University of Manchester, Manchester M13 9PL, UK
Author to whom correspondence should be addressed.
Informatics 2018, 5(1), 11;
Received: 28 November 2017 / Revised: 4 February 2018 / Accepted: 21 February 2018 / Published: 23 February 2018
(This article belongs to the Special Issue Using Computational Provenance)
Scientists routinely analyse and share data for others to use. Successful data (re)use relies on having metadata describing the context of analysis of data. In many disciplines the creation of contextual metadata is referred to as reporting. One method of implementing analyses is with workflows. A stand-out feature of workflows is their ability to record provenance from executions. Provenance is useful when analyses are executed with changing parameters (changing contexts) and results need to be traced to respective parameters. In this paper we investigate whether provenance can be exploited to support reporting. Specifically; we outline a case-study based on a real-world workflow and set of reporting queries. We observe that provenance, as collected from workflow executions, is of limited use for reporting, as it supports queries partially. We identify that this is due to the generic nature of provenance, its lack of domain-specific contextual metadata. We observe that the required information is available in implicit form, embedded in data. We describe LabelFlow, a framework comprised of four Labelling Operators for decorating provenance with domain-specific Labels. LabelFlow can be instantiated for a domain by plugging it with domain-specific metadata extractors. We provide a tool that takes as input a workflow, and produces as output a Labelling Pipeline for that workflow, comprised of Labelling Operators. We revisit the case-study and show how Labels provide a more complete implementation of reporting queries. View Full-Text
Keywords: workflow; provenance; domain-specific annotation workflow; provenance; domain-specific annotation
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MDPI and ACS Style

Alper, P.; Belhajjame, K.; Curcin, V.; Goble, C.A. LabelFlow Framework for Annotating Workflow Provenance. Informatics 2018, 5, 11.

AMA Style

Alper P, Belhajjame K, Curcin V, Goble CA. LabelFlow Framework for Annotating Workflow Provenance. Informatics. 2018; 5(1):11.

Chicago/Turabian Style

Alper, Pinar, Khalid Belhajjame, Vasa Curcin, and Carole A. Goble 2018. "LabelFlow Framework for Annotating Workflow Provenance" Informatics 5, no. 1: 11.

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